German physicians' expectations of healthcare management companies: An exploratory study

Abstract Background and aims Even 20 years after the introduction of managed care (MC) in Germany, many physicians are skeptical of the concept, hindering its acceptance. Methods Based on multivariate statistical methods this exploratory study examines how so‐called management companies, that is, administrative service providers within MC contracts, can increase physicians' acceptance of MC by offering, for example, day‐to‐day coordination and administrative tasks. Results As a main empirical result, we find support for this hypothesis, that is, that certain physicians evaluate their MC participation according to its prospective administrative support. Based on this, up to four clusters of physicians can be statistically identified in terms of their preferences regarding MC. Conclusion As a policy recommendation, we derive from our results that a future focus on the administrative support components of MC is essential to attract certain physician groups to participate in MC.

In fact, there are only few publications that address expectations of how MC should be organized and what elements MC should include from the perspective of potentially involved actors (e.g., 8 ; for a general discussion of the extant literature see Section 2.2 below).
To the best of our knowledge, there is no published paper to date on our specific research question, namely, what expectations health care providers have about the possibility of transferring management functions (e.g., ongoing organizational practice and billing tasks) to a so-called management company operating as an organizational or service unit within an MC contract. Consequently, this study asks where suitable areas of responsibility for management companies could lie from the perspective of healthcare service providers. Note that to analyze this question, we take a very broad view of MC 9,10 in line with German legal requirements (see § 140a SGB V, German Social Code, Book V). This means that in addition to its traditional focus on collaborative health care, we also emphasize the organizational and management aspect as a valid element of MC. Our findings provide important insights for designing MC contracts to be more incentive-compatible for physicians in the future. This would involve marketing management companies to physicians as a type of service provider that offers tangible benefits.
Examples include administrative support, financing, IT networking of physicians, or risk pooling. 11 Quantitative empirical research on this question is hardly available for Germany so far. Some findings on perceived importance and expectations of content-related MC aspects have been discussed, for example, by Refs. 6,7,10,12,13 Outside of the German healthcare system, there is some literature that addresses specific facets of MC management components. 14 Further studies in this context include selected aspects on data and information exchange 8,15 or the design of controlling aspects. [16][17][18][19] Based on a physician survey our paper applies an empirical factor and cluster analyses to identify major components of physicians' expectations from a healthcare management company associated with a MC-contract. The analysis also allows us to find several potentially latent groups of physicians based on these factors. From a health policy perspective, these findings can serve for target groupspecific communication with the medical profession and thus increase the attractiveness of MC participation. The data set is based on a structured telephone survey of 500 physicians with own practice in Northern Germany.
The remainder of the paper is organized as follows. Section 2 provides background information on the role of management companies in Germany and a literature review. Section 3 describes the data collection and the methodology used. The empirical results are presented in Section 4. Section 5 provides a discussion. Section 6 concludes.

| The role of management companies in German MC
Before going into more detail about the existing literature and the gap therein that leads to our research question, we will briefly discuss the specific understanding of MC in Germany compared to other countries. This is all the more important because our research question is also directly related to the relatively broad definition of MC in Germany. The latter allows the establishment of so-called management companies within MC as a German peculiarity (see § 140a SGB V). Management companies may provide unspecified administrative and organizational services to MC contract partners.
In the United States, for example, MC has been introduced since the 1970s mainly in terms of Health Maintenance (HMO) and Preferred Provider Organizations (PPO). While HMOs focus on the integration of insurance and provider activities within a single organization, PPOs manage the utilization of health care services within a provider network.
In German health care, similar attempts have been made to establish a stronger sectoral integration with the Social Health Insurance Reorganization Acts starting in 1997 (GKV-Neuordnungsgesetze). In particular, the subsequent reform attempts based on §140a (integrated/ special Care, IV), §137 f (disease management programs, DMP) and § §63-65 (model projects), SGB V, reflect a strengthening of care options in the sense of MC. The basic idea behind these reform approaches involves selective contracts between individual service providers, such as IV or DMP. For example, one aspect of these reform approaches is that utilization of services is controlled by financial or qualitative incentives (e.g., limiting the patient population to participants, continuing education requirements for physicians, referral only to network physicians, etc.).
The function of the management company as defined in §140a SGB V plays a special role in the design of these selective contracts.
In essence, the legislator is concerned to bring business expertise and coordination into selective care via management companies, thereby ensuring their economic survival in a competitive environment. 20 A broad interpretation of the term "management company" is obviously intended by the legislator. Since health care providers and insurers generally have little experience with MC in Germany, a division of labor with respect to management tasks seems reasonable. However, this is accompanied by an inherent conflict of interests between adequate service provision and cost-efficient management.
The pure service provider function may be contrasted with a more strategic function of the healthcare management companies. This view discusses the latter primarily as a central component of systemic innovation for healthcare systems. This involves a patient-oriented reorganization of the individual delivery of healthcare services. Here, management companies provide additional services such as patient coaches and appointment management. They may also serve as an additional intermediary between service providers and health insurers.
In this way, budget control and contract management can be complemented by population and information pooling. An example of this more strategic role for management companies is provided by OptiMedis AG. 21 In the following section, we will briefly discuss that the preferred role of management companies from the physicians' perspective is a promising research question that has not yet been addressed widely in the literature to date. Another important aspect from the perspective of participating physicians is the fact that they associate MC contracts with an option to secure their economic future. Network participants primarily expect better treatment quality, followed by uniform treatment standards, modernization impulses, and positive income effects.

| Literature review and research approach
The overview discussion of the literature above reveals a certain research gap in three respects, which our paper addresses. First, the importance of different management components associated with MC is generally omitted in favor of, for example, the medical and monetary aspects of MC. Second, most studies that address management aspects of MC are limited to qualitative approaches that, unlike our paper, do not allow for multivariate analyses, see e.g.
Weinmayr et al. 25 Finally, none of the previous studies focuses on the heterogeneity of physicians in terms of their expectations of MC.
However, it is the analysis of this physician heterogeneity, which we will discuss in Sections 4 to 6, that will enable policymakers to advance MC adoption in a more target-group-specific manner than has been the case to date.

| Sample and data
The data we use is based on a CATI (Computer-assisted telephone interviewing) survey of 504 physicians in private practice in Northern Germany, that is, Lower Saxony, Schleswig-Holstein, Hamburg, and Bremen. The region includes a mix of rural and urban areas with three major metropolitan areas. For a critical discussion of this method, see Refs. 32,33 The survey was conducted between August and September 2014 based on a population of approximately 6000 telephone register data. Twenty-seven professional interviewers trained for the project were employed and conducted the telephone OBERSCHACHTSIEK AND EHLERT | 3 of 11 survey between 8:00 a.m. and 8:00 p.m. on all days of the week. On average, seven contacts were required for a successful telephone interview, which lasted 15-16 min on average. Participation was refused in 3469 cases. Other dropouts were related to "not reached" (n = 808), "answering machine" (n = 950), "appointment but no one reached" (n = 188), "repeatedly busy" (n = 26), and "dropout without continuation" (n = 14). Regarding the participation rate, it should be considered that no compensation was granted. The limited accessibility of physicians for an interview is also reflected in the relatively high median of six contact attempts for a successful interview.
The distribution of the characteristics gender, age, specialist qualification and single practice largely corresponds to the structural characteristics of all physicians in private practice in Germany. 34 About 68% of the surveyed participants were specialists, the rest were family physicians.

| Measures and variables
The focus of the survey is the cooperation and networking behavior between physicians in private practice with other health care providers. All physicians were asked whether they were already involved in certain forms of cooperation and MC. In addition, general structural information on practice and professional orientation was collected. The questionnaire, which was developed specifically for the project itself, considered the results of a qualitative preliminary study. The questionnaire was finally validated with a pretest (n = 40) under practical conditions.
The sample was split for more in-depth focus surveys. In one of these focus surveys, a total of 95 physicians were asked which services they would like to see management companies take over when it comes to collaborating with other health care providers within MC. Respondents were given a list of possible tasks to evaluate. Specifically, the survey stated, "Imagine you decide to collaborate with others. A coordination office is to be established to support this endeavor. This coordination office can now have different focal points of work. How important do you consider the following tasks on a scale from 1 = completely unimportant to 5 = very important?" The following services were listed: • It helps to solve the documentation tasks better • It implements case management • It coordinates appointments with specialist colleagues for faster diagnoses • It advises and supports patients, for example, in questions of their treatment organization • It organizes specialist circles and case discussions • It helps to avert problem cases and recourse risks • It is responsible for administrative tasks.

| Data analysis procedure
Our data analysis procedure can be divided into four steps. In the first step, we perform summary descriptive analyses of the responses in tabular form (including mean and standard deviation, SD). In the second and third steps, we perform a multivariate analysis of the responses to find latent structures that help us to characterize groups of physicians that are homogeneous in terms of their expectations as to the management component of MC. Steps 2 and 3 have been carried out with the Stata 16 software. 35 A factor analysis (Step 2) to search for latent characteristics is followed by a cluster analysis (Step 3) to identify potential groups of physicians with similar expectations as to management companies. The cluster analysis first uses the results of an agglomerative-hierarchical procedure to identify the optimal number of existing groups in the data. It then applies a kmeans analysis to obtain a cluster-assignment of the investigated physicians. In a fourth step, these clusters are characterized for ease of interpretation using summary data for the practice manager (physician) and the practice itself.

| Dimensions of expectations
The starting point is a principal factor analysis 36 based on the seven characteristics used to determine the management company's "desired focus of work," see Section 3.2. The measure of sampling adequacy according to Kaiser-Meyer-Olkin (with a value of 0.87 for all included characteristics) confirms a latent data structure. 37 The Bartlett test of sphericity also confirms the suitability of the data for factor analysis. It turns out that based on the Kaiser criterion, a onefactor solution is the preferred data representation.
A complementary principal-component factors solution 36 shows that considering a second factor provides an additional variance coverage of 11.47% (first factor: 61.42%). Moreover, the information score in the model comparison is highest for the two-factor solution (lowest AIC and BIC values). Therefore, the two-factor solution is used throughout the rest of the analysis.
The factor table obtained after varimax rotation (see Table A1, factor loadings below 0.3 are suppressed) shows that Factor 1 captures the expectations "documentation" (factor loading 0.838), "appointment coordination" (factor loading 0.751) and "administration" (factor loading 0.727). The interpretation is that the factor represents a bundle of expectations in the direction of "administrative process support". Note that with a Cronbach's alpha of 0.874 we obtain sufficient support for our general interpretation of this factor.

Factor 2, by contrast, can be interpreted as (a bundle of) expectations
for "extended treatment support" (with factor loadings of 0.695 on "treatment organization" and 0.501 on "specialist circles"). With respect to its internal consistency, we find an acceptable Cronbach's alpha of 0.671 (where adding the variable "recourse defense" to the factor would produce a Cronbach's alpha of 0.740).
As a robustness check we allowed both factors to be interrelated (using Stata's rotation procedure "oblimin oblique"). Then, the variables "specialist circles" and "case management" have considerably higher relevance for the second factor. The relevance of the core characteristics identified in orthogonal rotation also increases.
Overall, the representation of the factors in terms of content remains the same for different rotation procedures. The robustness of the results is also underlined by the fact that all common rotation methods support a two-factor solution.

| Physician groups with different expectations
The starting point for the cluster analysis is an agglomerativehierarchical approach. The results of the procedure are summarized in the dendrogram in Figure 1. As can be seen, the inequality increases especially in the penultimate merger stage, which indicates a four-cluster solution. Against this background, the clusters labeled G1 to G5, G6 to G9, G10 to G12, and G13 to G15 in the figure appear to represent similar groups. However, the degree of dissimilarity only increases substantially in the last stage, so that a three-cluster solution could also be considered (G1 to G5, G6 to G9, and G10 to G15). Note that a two-cluster solution does not seem to be a suitable solution according to the elbow criterion.
In addition, Table A2 shows statistical indicators that can be used to identify the optimal number of clusters based on the Calinski/ Harabasz pseudo-F statistic and based on the Duda/Hart index. 38 High values represent distinct clusters. Both the Calinski/Harabaszpseudo-F statistic and the Duda/Art statistic support the above argumentation regarding a three-to four-cluster solution in the data.
For the second step, the procedure according to the kmeans method (Euclidian distance) for the three-and four-cluster solution is shown in Figures 2 and 3. Table 3  Regarding the three-cluster solution, we find cluster 3/1 to be a group with predominantly negative factor loadings on both extracted factors.
In terms of content, this group thus has fundamentally low approval ratings for management services in the context of cooperation with  F I G U R E 3 Factor scores for the four-cluster solution other service providers and can best be described as a "rejection group." Cluster 3/2, on the other hand, contains observations with negative factor loadings for factor 2, while at the same time having positive factor loadings for factor 1. Hence, this cluster corresponds to a group of physicians with high agreement on administrative services in MC, but at the same time with lower agreement on professional-oriented support services (represented by factor 1). It could be described as a "management group." Finally, the third cluster 3/3 includes observations with mixed positive and negative factor loadings with respect to both factors. Table 3 shows that in cluster 3/3 the support components case management, treatment organization, and recourse defense have the highest agreement values. This stands in contrast to cluster 3/2 where administration, documentation, and appointment coordination show high agreement, while treatment organization and case management exhibit low to moderate agreement. As expected, Table 3  less need for specialist support, but is more in favor of administrative services, that is, a "management group." As with the three-cluster solution, this picture is also reflected in the average approval ratings for the support components under consideration (see Table 3, bottom section).
A multivariate analysis of variance also confirms statistically significant differences at the 99% level between the groups in the three-and four-cluster solutions. However, the test requirements regarding interval scaling, normal distribution of the factor values and equal distribution in the groups are only partially met. Overall, however, the complementary tests favor the four-cluster over the three-cluster solution.

| Cluster typology
To further characterize the clusters, Table 4 provides an overview of descriptive statistics for selected characteristics of the physicians included in the study based on the clusterassignment of the kmeans procedure. In contrast to Table 3 Interestingly, however, an almost similar picture is also found for the additional cluster of the four-cluster solution (cluster with comparatively higher agreement for professional support).

| DISCUSSION
The A key finding of our study is that the empirical analysis reveals two factors regarding physicians' preferences for MC. The first can be described as "administrative process support" and the second as In addition to providing the first quantitative assessment and multivariate analysis of such outcomes, our study also goes one step further by providing a data-based typology of physicians with respect to these two factors. In this context, the assignment of physicians to one of the identified clusters reflects a disclosure of their preference, see for example, Zonneveld et al. 45  However, the very broad regional selection of physicians surveyed and the stability of the quantitative results in several statistical robustness checks (e.g., different rotation approaches and exclusion criteria in the factor analysis as well as different cluster solutions) suggest a high degree of stability and thus wide applicability of our results. visualization; writing-original draft; writingreview and editing.

ACKNOWLEDGMENTS
We would like to thank three anonymous referees for their valuable comments that helped to improve earlier versions of this study. We would also like to thank the participating physicians for their time and commitment, without which this study would not have been possible.
Open Access funding enabled and organized by Projekt DEAL.

DATA AVAILABILITY STATEMENT
The data that support the findings of this study are available from the corresponding author upon request.

CONFLICT OF INTEREST
The authors declare no conflict of interest.

TRANSPARENCY STATEMENT
The lead author Dirk Oberschachtsiek, Andree Ehlert affirms that this manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned (and, if relevant, registered) have been explained.